Rationalization design, soluble expression and PEG modification of highly active recombinant human-porcine uricase mutant protein.

Uric acid is the end product of purine metabolism in humans due to inactivation of the uricase determined by the mutated uricase gene. Uricase catalyzes the conversion of uric acid into water-soluble allantoin that is easily excreted by the kidneys. Hyperuricemia occurs when the serum concentration of uric acid exceeds its solubility (7 mg/dL). However, modifications to improve the uricase activity is under development for treating the hyperuricemia. Here we designed 7 types of human-porcine chimeric uricase by multiple sequence comparisons and targeted mutagenesis. An optimal human-porcine chimeric uricase mutant (uricase-10) with both high activity (6.33 U/mg) and high homology (91.45 %) was determined by enzyme activity measurement. The engineering uricase was further modified with PEGylation to improve the stability of recombinant protein drugs and reduce immunogenicity, uricase-10 could be more suitable for the treatment of gout and hyperuricemia theoretically.

Global transcriptional program of p53 target genes during the process of apoptosis and cell cycle progression.

The temporal gene expression profile during the entire process of apoptosis and cell cycle progression in response to p53 in human ovarian cancer cells was explored with cDNA microarrays representing 33 615 individual human genes. A total of 1501 genes (4.4%) were found to respond to p53 (approximately 80% of these were repressed by p53) using 2.5-fold change as a cutoff. It was anticipated that most of p53 responsive genes resulted from the secondary effect of p53 expression at late stage of apoptosis. To delineate potential p53 direct and indirect target genes during the process of apoptosis and cell cycle progression, microarray data were combined with global p53 DNA-binding site analysis. Here we showed that 361 out of 1501 p53 responsive genes contained p53 consensus DNA-binding sequence(s) in their regulatory region, approximately 80% of which were repressed by p53. This is the first time that a large number of p53-repressed genes have been identified to contain p53 consensus DNA-binding sequence(s) in their regulatory region. Hierarchical cluster analysis of these genes revealed distinct temporal expression patterns of transcriptional activation and repression by p53. More genes were activated at early time points, while more repressed genes were found after the onset of apoptosis. A small-scale quantitative chromatin immunoprecipitation analysis indicated that in vivo p53-DNA interaction was detected in eight out of 10 genes, most of which were repressed by p53 at the early onset of apoptosis, suggesting that a portion of p53 target genes in the human genome could be negatively regulated by p53 via sequence-specific DNA binding. The approaches and genes described here should aid the understanding of global gene regulatory network of p53.

Human survivin is negatively regulated by wild-type p53 and participates in p53-dependent apoptotic pathway.

Survivin is an inhibitor of apoptosis protein, which is over-expressed in most tumors. Aberrant expression of survivin and loss of wild-type p53 in many tumors prompted us to investigate a possible link between these two events. Here we show that wild-type p53 represses survivin expression at both mRNA and protein levels. Transient transfection analyses revealed that the expression of wild-type p53, but not mutant p53, was associated with strong repression of the survivin promoter in various cell types. The over-expression of exogenous survivin protein rescues cells from p53-induced apoptosis in a dose-dependent manner, suggesting that loss of survivin mediates, at least, in part the p53-dependent apoptotic pathway. In spite of the presence of two putative p53-binding sites in the survivin promoter, deletion and mutation analyses suggested that neither site is required for transcriptional repression of survivin expression. This was confirmed by chromatin immunoprecipitation assays. Further analyses suggested that the modification of chromatin within the survivin promoter could be a molecular explanation for silencing of survivin gene transcription by p53.

Comparative promoter analysis and its application in analysis of PTH-regulated gene expression.

Taking advantage of the "working draft" of the human genome and the MIT shotgun assembly of the mouse genome, we performed a comparative promoter analysis of human RefSeq mRNA (sequences from GenBank's RefSeq database). By combining this analysis with a transcription factor (TF) binding site analysis using a TRANSFAC position weight matrix (PWM) search, 86% of non-specific TF sites were removed. Using a set of genes that are regulated by parathyroid hormone (PTH), a statistical analysis was performed on the conserved TF binding sites among a set of eight human and mouse genes. From among the eight genes tested, we obtained a set of 31 TFs, suggesting possible roles for associated genes in PTH-mediated pathways. All three known PTH-responsive TFs (AP1, RUNX2, CREB) were correctly predicted by this analysis as well as two other potential TFs (VDR and CEBP Delta). Additionally, a model was made to describe the TF site characteristic module of PTH-regulated genes. This model was then used to search all human RefSeq gene promoters with established human-mouse ortholog relationships to identify other PTH-regulated genes. This comparative approach combined with statistical analysis proved to be sufficiently specific to decipher critical TFs involved in PTH-regulated pathways.

Analysis of the ERK1,2 transcriptome in mammary epithelial cells.

MAPK (mitogen-activated protein kinase) pathways constitute major regulators of cellular transcriptional programmes. We analysed the ERK1,2 (extracellular-signal-regulated kinase 1,2) transcriptome in a non-transformed MEC (mammary epithelial cell) line, MCF-12A, utilizing rAd MEK1EE, a recombinant adenovirus encoding constitutively active MEK1 (MAPK/ERK kinase 1). rAd MEK1EE infection induced morphological changes and DNA synthesis which were inhibited by the MEK1,2 inhibitor PD184352. Hierarchical clustering of data derived from seven time points over 24 h identified 430 and 305 co-ordinately up-regulated and down-regulated genes respectively. c-Myc binding sites were identified in the promoters of most of these up-regulated genes. A total of 46 candidate effectors of the Raf/MEK/ERK1,2 pathway in MECs were identified by comparing our dataset with previously reported Raf-1-regulated genes. These analyses led to the identification of a suite of growth factors co-ordinately induced by MEK1EE, including multiple ErbB ligands, vascular endothelial growth factor and PHRP (parathyroid hormone-related protein). PHRP is the primary mediator of humoral hypercalcaemia of malignancy, and has been implicated in metastasis to bone. We demonstrate that PHRP is secreted by MEK1EE-expressing cells. This secretion is inhibited by PD184352, but not by ErbB inhibitors. Our results suggest that, in addition to anti-proliferative properties, MEK1,2 inhibitors may be anti-angiogenic and possess therapeutic utility in the treatment of PHRP-positive tumours.

Analysis of a human brain transcriptome map.

BACKGROUND: Genome wide transcriptome maps can provide tools to identify candidate genes that are over-expressed or silenced in certain disease tissue and increase our understanding of the structure and organization of the genome. Expressed Sequence Tags (ESTs) from the public dbEST and proprietary Incyte LifeSeq databases were used to derive a transcript map in conjunction with the working draft assembly of the human genome sequence. RESULTS: Examination of ESTs derived from brain tissues (excluding brain tumor tissues) suggests that these genes are distributed on chromosomes in a non-random fashion. Some regions on the genome are dense with brain-enriched genes while some regions lack brain-enriched genes, suggesting a significant correlation between distribution of genes along the chromosome and tissue type. ESTs from brain tumor tissues have also been mapped to the human genome working draft. We reveal that some regions enriched in brain genes show a significant decrease in gene expression in brain tumors, and, conversely that some regions lacking in brain genes show an increased level of gene expression in brain tumors. CONCLUSIONS: This report demonstrates a novel approach for tissue specific transcriptome mapping using EST-based quantitative assessment.

Domain-oriented functional analysis based on expression profiling.

BACKGROUND: Co-regulation of genes may imply involvement in similar biological processes or related function. Many clusters of co-regulated genes have been identified using microarray experiments. In this study, we examined co-regulated gene families using large-scale cDNA microarray experiments on the human transcriptome. RESULTS: We present a simple model, which, for each probe pair, distills expression changes into binary digits and summarizes the expression of multiple members of a gene family as the Family Regulation Ratio. The set of Family Regulation Ratios for each protein family across multiple experiments is called a Family Regulation Profile. We analyzed these Family Regulation Profiles using Pearson Correlation Coefficients and derived a network diagram portraying relationships between the Family Regulation Profiles of gene families that are well represented on the microarrays. Our strategy was cross-validated with two randomly chosen data subsets and was proven to be a reliable approach. CONCLUSION: This work will help us to understand and identify the functional relationships between gene families and the regulatory pathways in which each family is involved. Concepts presented here may be useful for objective clustering of protein functions and deriving a comprehensive protein interaction map. Functional genomic approaches such as this may also be applicable to the elucidation of complex genetic regulatory networks.

A reference database for tumor-related genes co-expressed with interleukin-8 using genome-scale in silico analysis.

BACKGROUND: The EST database provides a rich resource for gene discovery and in silico expression analysis. We report a novel computational approach to identify co-expressed genes using EST database, and its application to IL-8. RESULTS: IL-8 is represented in 53 dbEST cDNA libraries. We calculated the frequency of occurrence of all the genes represented in these cDNA libraries, and ranked the candidates based on a Z-score. Additional analysis suggests that most IL-8 related genes are differentially expressed between non-tumor and tumor tissues. To focus on IL-8's function in tumor tissues, we further analyzed and ranked the genes in 16 IL-8 related tumor libraries. CONCLUSIONS: This method generated a reference database for genes co-expressed with IL-8 and could facilitate further characterization of functional association among genes.

Hepatitis C virus whole genome position weight matrix and robust primer design.

BACKGROUND: The high degree of sequence heterogeneity found in Hepatitis C virus (HCV) isolates, makes robust nucleic acid-based assays difficult to generate. Polymerase chain reaction based techniques, require efficient and specific sequence recognition. Generation of robust primers capable of recognizing a wide range of isolates is a difficult task. RESULTS: A position weight matrix (PWM) and a consensus sequence were built for each region of HCV and subsequently assembled into a whole genome consensus sequence and PWM. For each of the 10 regions, the number of occurrences of each base at a given position was compiled. These counts were converted to frequencies that were used to calculate log odds scores. Using over 100 complete and 14,000 partial HCV genomes from GenBank, a consensus HCV genome sequence was generated along with a PWM reflecting heterogeneity at each position. The PWM was used to identify the most conserved regions for primer design. CONCLUSIONS: This approach allows rapid identification of conserved regions for robust primer design and is broadly applicable to sets of genomes with all levels of genetic heterogeneity.

Genome wide in silico SNP-tumor association analysis.

BACKGROUND: Carcinogenesis occurs, at least in part, due to the accumulation of mutations in critical genes that control the mechanisms of cell proliferation, differentiation and death. Publicly accessible databases contain millions of expressed sequence tag (EST) and single nucleotide polymorphism (SNP) records, which have the potential to assist in the identification of SNPs overrepresented in tumor tissue. METHODS: An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106). RESULTS: A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigation CONCLUSIONS: This novel in silico approach can assist in prioritization of genes and SNPs in the effort to elucidate the genetic mechanisms underlying the development of cancer.

Generation of p53 target database via integration of microarray and global p53 DNA-binding site analysis.

The completion of the human genome sequence and availability of cDNA microarray technology provide new approaches to explore global cellular regulatory mechanisms. Here we present a strategy to identify genes regulated by specific transcription factors in the human genome, and apply it to p53. We first collected promoters or introns of all genes available using two methods: GenBank annotation and a computationally derived transcript map. The "FindPatterns" program is then used to search sequences in regulatory regions that match the p53 DNA-binding consensus sequence, resulting in the p53 Target Database. This database collects human genes that have at least one p53 DNA-binding sequence in their regulatory region. cDNA microarray was also used to identify genes that respond to p53 at a genomic scale. Integration of the microarray data and the p53 Target Database should greatly enrich direct p53 target genes. Taqman analysis and quantitative chromatin immunoprecipitation analysis are used to validate the in silico prediction and microarray data. Enrichment factor analysis is used to demonstrate that in silico prediction greatly enriches for genes that are transcriptionally regulated by p53 and assists us to identify other signaling pathways that are potentially connected to p53. The approaches can be extended to other transcription factors. The methods shown here illustrate a novel approach to the analysis of global gene regulatory networks through the integration of human genomic sequence information and genome-wide gene expression analysis.

[IRE_FINDER-computational search of iron response element in human and mouse UTRs].

The iron response element (IRE) is a highly conserved RNA stem loop structure. It is the binding site of iron regulatory protein (IRP). IRP binding to IRE is regulated by cellular iron. When cells are derived of iron, IRP binds IRE. If IRE is located at 5'UTR, IRP binding will inhibit translation initiation, else if IRE is at 3'UTR, IRP binding will stabilize mRNA and prevent it from degradation. So far all known IREs have C at the 1 position and G at the 5 position of the loop (C1G5 type). In vitro studies suggest that the U1A5 type IRE, which has U and A at the 1 and 5 loop position respectively, binds well to IRP. However, U1A5 type's in vivo existence is still elusive. IRE-IRP binding is involved in the regulation of iron metabolism, oxidative stress and possibly aging. Here we use an improved computation method performing a comprehensive search of IRE in human and mouse genes. We try to catalog potential human and mouse IRE containing genes, at the same time identify potential U1A5 IREs.

A Web-based design center for vector-based siRNA and siRNA cassette.

SUMMARY: To facilitate the designing process for vector-based siRNA and siRNA cassette, a tool set has been developed consisting of a siRNA target finder, a siRNA construct builder and a siRNA sequence scrambler. The siRNA target finder is used to identify candidate siRNA target sites. The program automates homology filtering, minimizes non-specific cross-reaction, filters target sites based on RNA duplex internal stability and siRNA sense/anti-sense strand secondary structure. The siRNA construct builder is used to create a siRNA hairpin construct as a vector insert or a cassette insert. The siRNA sequence scrambler is used to generate a negative control sequence for siRNA experiments. Together, these programs provide a comprehensive utility set to address the specific bioinformatics need of DNA-based siRNA design. AVAILABILITY: The Web-based design tools are available at GenScript Website (siRNA design center). http://www.genscript.com or http://www.genscript.com/rnai.html#design or http://www.genscript.com/sirna_ca.html#design

A new lactone from Senecio cannabifolius Less.

A new lactone compound named cannabifolactone A was isolated from the water extract of the aerial parts of Senecio cannabifolius Less. Its structure was elucidated mainly by 1D- and 2D-NMR techniques.

Transforming growth factor-beta 2 is a transcriptional target for Akt/protein kinase B via forkhead transcription factor.

Tumors evade cell death by constitutively activating cell survival pathways and suppressing intrinsic death machinery. Activation of cell survival pathways leads to transcriptional repression of genes associated with cell death and activation of ones promoting anti-apoptosis. Akt/protein kinase B phosphorylates forkhead transcription factors and prevents their nuclear localization, leading to repression of genes involved in apoptosis, such as Fas ligand (FasL). Using bioinformatic approaches, we have identified three consensus sequences for forkhead transcription factor binding in transforming growth factor beta2 (TGF-beta2) promoter. TGF-beta inhibits cell proliferation and induces apoptosis in many cell types, and acquisition of TGF-beta resistance is linked to tumorigenesis. In this study, we show that activated Akt down-regulates TGF-beta2 promoter, and sequences within the promoter that are related to consensus forkhead binding sites are necessary for repression. Forkhead factor FKHRL1 binds in vitro to the three consensus sequences and can activate TGF-beta2 promoter in normal and Akt-transformed cell lines. In human breast and pancreatic tumors, activated Akt expression correlated with down-regulation of TGF-beta 2 mRNA levels. A number of tumor cells expressing activated Akt were responsive to TGF-beta addition, indicating the presence of an intact TGF-beta-signaling pathway. These results suggest that repression of TGF-beta 2 promoter activity in cells expressing activated Akt may play a role in promoting tumorigenesis and escape from the growth-inhibitory and/or apoptotic effects of TGF-beta.

Computational analysis of composite regulatory elements.

Combinatorial regulation is a powerful mechanism for generating specificity in gene expression, and it is thought to play a pivotal role in the formation of the complex gene regulatory networks found in higher eukaryotes. The term "Composite Element" (CE) refers to a minimal functional unit where protein-DNA and protein-protein interactions contribute to a highly specific pattern of gene transcriptional regulation. Identification of composite elements will help to better understand gene regulation networks. Experimentally identified CEs are limited in number, and the currently available CE database COMPEL is based on such published information. Here, based on the statistical analysis of over-represented adjacent transcription factor binding sites, we describe a computational method to predict composite regulatory elements in genomic sequences. The algorithm proved to be efficient for extracting composite elements that had been experimentally confirmed and documented in the COMPEL database. Furthermore, putative new composite elements are predicted based on this method, and we have been able to confirm some of our predictions which are not included in the COMPEL database by searching published information.

Gene expression profiles and transcription factors involved in parathyroid hormone signaling in osteoblasts revealed by microarray and bioinformatics.

Parathyroid hormone (PTH) binds to its receptor PTH1R (parathyroid hormone 1 receptor) in osteoblastic cells to regulate bone remodeling and calcium homeostasis. While prolonged exposure to PTH causes increased bone resorption, intermittent injections of PTH have an anabolic effect on bone. The molecular mechanisms regulating these processes are still largely unknown. Here, we present our results on gene expression profile changes in the PTH-treated osteoblastic cell line, UMR 106-01, using DNA microarray analysis. A total of 125 known genes and 30 unknown expressed sequence tags (ESTs) were found to have at least 2-fold expression changes after PTH treatment at 4, 12, and 24 h. 14 genes were previously known to be PTH-regulated but many were unknown to be regulated by PTH prior to our experiments. Real-time reverse transcriptase-PCR confirmed that 90 and 50% of the genes are regulated more than 2-fold by PTH in UMR 106-01 and rat primary osteoblastic cells, respectively. Most genes belong to the following protein families: hormones, growth factors, and receptors; signal transduction pathway proteins; transcription factors; proteases; metabolic enzymes; structural and matrix proteins; transporters; etc. These results provide a comprehensive and deeper knowledge about PTH regulation of osteoblastic gene expression. Next, we designed a computational method to extract information about transcription factors likely involved in regulating these genes. These factors include those previously known to be involved in PTH signaling (AP-1 and the cAMP response element-binding protein), those that were identified by microarray data (C/EBP), and some novel transcription factors (AP-2, AP-4, SP1, FoxD3, etc.). Our results suggest that a reliable bioinformatics approach can be easily applied for other systems.